MatLab is a predictive analytics and computing platform based on a proprietary programming language. MatLab is used across industry and academia.
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Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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Chose MATLAB
Those are expensive than MATLAB and their GUI is not great along with editor. However, they have more libraries set as compared to Matlab. However, the place where MATLAB adds value is its user community as well as its support and we can find solutions to any problem with …
Apart from Matlab, I used Matematica for some of my integral evaluations. Mathematica is also a "clean" and easy-to-use software that solves symbolic math problems (even better than Matlab for symbolic math). I also used Anaconda and Spyder for my career so far.
The commands and coding language of MATLAB reads a lot more in plain English as opposed to all the periods and other special characters that are needed when typing in Python or Java. Additionally MATLAB has several different function packages that can solve all different …
MATLAB's neurophysiological data pre-processing third-party packages are more scientifically validated compared to support for other software platforms. It also allows for writing code with a greater level of functionality and more capabilities than R-Studio, which is instead …
It seems MATLAB has built-in functionality that is sometimes missing in Spotfire and can only be enabled in Spotfire with additional programming language like Iron Python.
MATLAB provides a variety of options for development. The other tools or I can say simulators do not provide major functionalities as provided by MATLAB as it is used in many fields. This is one tool which is used for research and development purpose. It gains popularity with …
GNU Octave is a widely used alternative to MATLAB which is free. I use MATLAB because I've been using it since I learned how to use it in my undergraduate. Furthermore, paid applications offer more support and oftentimes, more updates than open source software.
While not as fully featured as other software suites. MATLAB benefits from a short learning curve while still allowing teams to build robust algorithms in short amounts of time.
I have not used any other products like MATLAB. I have used this software for almost ten years now and it hasnt let me down. I want to learn new open source coding platforms but for now MATLAB serves all my needs and purposes.
For complex calculations, go with MATLAB; I can't even think of how it could be done in Tableau. But if one is not familiar with scripting and only wants to visualize data with minimal wrangling, Tableau will work just fine and comes back with graphics comparable or even better …
MatLab is better than Phython in terms of robustness of its tools, help library, online community, library of tools, ease of programming (simpler and more intuitive syntax), ease of installation and after sale service. These are really significant advantages and they are the …
How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended …
MATLAB is easier to use than a program like LabVIEW. What LabVIEW lacks in simplicity, however; it makes up for in functionality. There are many programs that can do a lot more than MATLAB can. That being said, if you are looking for the easiest and most convenient way to …
Every product has its own advantages and disadvantages. MATLAB is one which can be understood easily and fast and so that would be a reason to select it.
Pycharm is a python coding platform, however, it is not very user-friendly. You need to know the syntax, characters, and other libraries to use it appropriately. I had difficulty understand these problems with Pycharm whereas MATLAB is very easy to use as a calculator machine. …
MATLAB has a very large database of embedded functions and it is continually growing. Graphics processing is much easier than other similar product for beginners (such as Jupyter notebook and Python). Although it is not an open-source language, lots of learning materials and …
MATLAB is extremely more user friendly than Python. Especially for engineers and scientists. With Python you need to have additional packages to do scientific computing.
SPSS is good for folks who are not as familiar with statistics, and for those who are older or more technologically-experienced and may be overwhelmed by Posit's products. It's also really great for teaching students and getting them exposed. However, because Posit is free, …
Posit is far better than Jupyter Notebook and Minitab in this regard that Posit is actually capable of doing all kind of analytical stuffs like data pre-processing, wrangling, validation and visualization. On the other hand, Jupyter Notebook can be used for python programming …
Posit is way way way more reliable than Excel for anything more involved than a quick spreadsheet. Faster speeds, greater charting abilities, flexible functionality and more efficient memory usage. Python is still my go-to for anything that needs integration, but Posit beats …
I've used ArcGIS and ESRI for similar analysis and while both have their advantages, RStudio is much better suited for running advanced statistics and processing large volumes of data. It can also produce quality maps, however, for visually attractive maps and graphs, ArcGIS is …
RStudio is better than python for visualizations but it is less common to use it in many organizations. Excel and PowerBI are better for visualization but, they can only be used for simple models. I would choose R Studio for statistical analysis, ML, or DL because the language …
RStudio works really well compared to competitors such as Jupyter Notebook where there is no environment to visualize variables. RStudio on the other hand is much easier to use and provides the right set of environments for users.
inter-departmental collaboration - my first choice would be TIBCO Spotfire natural language processing and knowledge graphs - my first choice would be Python information security & visualizations (including d3.js libraries) - my first choice is RStudio
RStudio is more than a home for a dashboard. It is a content management system for data science. It hosts models, APIs, runs scripts, AND hosts dashboards.
RStudio stacks up pretty well against its competition. For me, it is really up to personal preference and what you are used to when deciding between the competitions. I like that Python packages have the most external resources, so it's easier to troubleshoot. But RStudio does …
The most similar products to RStudio that I have used include IBM SPSS and Tableau Prep. In my experience, SPSS is more intuitive and has less of a learning curve; I used it extensively in my undergraduate career in Statistics and Cognitive Science research. While RStudio has …
RStudio stacks up pretty well against Anaconda. However, Anaconda might be the first choice for someone who likes Python for their analytics and machine learning needs. In the past, I have found it seamless to connect Jupyter Notebook (in Anaconda suite) to integrate with other …
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful …
Personally, I would prefer SPSS over RStudio and SAS, but the cost for licenses for SPSS deters me from continuing to go with IBM's statistics software. RStudio has the advantage in that it is low cost and there are a lot of available resources on YouTube available for users …
Using [RStudio] requires greater knowledge of statistics and code than SPSS, which has a more simple "point and click" interface. [RStudio] is similar to SAS in its user interface and [requires] the user to write their own queries. [RStudio]'s main advantage is an open-source …
I tried Stata because it's a standard tool for economists but it doesn't have the flexibility and breadth of R and RStudio. I didn't try other IDEs for R.
RStudio is free and so that is the main reason that I use it. I like that it is open source and so there are lots of support on the internet. I tried SAS JMP and Python in a text editor but RStudio was better than either of those options for cost and code flexibility …
RStudio is as good as any software available in the market and is better off than some as it is free. Since it is open source it is improving day by day. I would prefer RStudio over any other tool any day. I would recommend every data analyst to give RStudio a try.
I understand the Jupyter notebook is supposed to be good like RStudio, and I've been exposed to it a little bit. But my experience using it has been very little.
I prefer SPSS to RStudio, but RStudio is very cheap in comparison to the cost of SPSS. IBM's SPSS does a better job holding the hands of users, but it does come at a very expensive license cost. RStudio is a little bit more difficult to use but is cheap.
These all work synergistically and fulfill slightly different roles. In general this is determined by complexity of task and the degree of training and expertise of the end user. RStudio works well for organisations looking to move into doing more complex analytics. In general …
There are loads of people in the BI (Business Intelligence) space, of course... but I wouldn't touch any of them because none of them offer anything like the R and Python support that RStudio does. RStudio publishes open-source, they're a public benefit corporation, and they …
Engineering, mathematical modeling, and machine learning are all fields where MATLAB will shine. It's fast, reliable, and relatively easy to use. MATLAB is the de facto standard when it comes to producing high-quality plots. If you need to deal with large data sets, and not take forever processing them, MATLAB may very well be the tool for you!
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
Has robust and easy-to-use debugging tools that can help one identify problems in one's codes.
Rich, well-developed and efficient library of mathematical and statistical functions that one might need to develop models or perform statistical analysis.
A very active online user community that is a great resource in terms of seeking help when you hit a snag.
Great help literature (and sometimes videos too) on all tools making it possible for all to train themselves.
MATLAB should have a full free version (without time limit) in order to be more accessible and thus have a greater user community.
The idea of having toolboxes to work directly with hardware (microcontrollers, single-board computers) is great, but one can tell it isn't updated very frequently and there isn't as much documentation available as with more common resources.
Our organization had a lot of trouble getting our network licenses to work properly and there wasn't any local service provider that could help us get it to work faster.
Ability to scale across the company is limited based on the users license, cannot share a dashboard to the general view of the company.
Ability to retain session - not simple method to customize view per user (e.g., once session is ended, the users will return next time to the baseline view).
Ability to enable communication between multiple users - leave notes, tag other users, or share specific view.
There is no other platform that meets our needs. Even if it was terrible we would still use it but fortunately for us it is a very solid project with a great support team. I hope in the future to expand our use and get more licences as well as upgrade to RStudio workbench but for now we are very happy.
The best thing about MATLAB is the variety of research and development fields it supports. The reason for this rating is that it is best used for medical images enhancement and signal processing, it is also used for speech to text conversion. This tool server is best when the demand is for machine learning.
For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
The commands and coding language of MATLAB reads a lot more in plain English as opposed to all the periods and other special characters that are needed when typing in Python or Java. Additionally MATLAB has several different function packages that can solve all different categories of problems so you don't have to make a bunch of different code scrips from scratch.
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
I think that RStudio scales pretty well based on the size of the datasets I'm using. It has multithreading capabilities unlike some other statistical analysis programs which is very useful in cutting down on time. The format of RStudio's syntax also makes it very easy to replicate regardless off the scale of the analysis and data set
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).